The Intelligent Sizing Method for Renewable Energy Integrated Distribution Networks
The selection of the optimal 35 kV network structure is crucial for modern distribution networks. To address the problem of balancing investment costs and reliability benefits, as well as to establish the target network structure, firstly, the investment cost of the distribution network is calculate...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/17/22/5763 |
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| _version_ | 1850216599054712832 |
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| author | Zhichun Yang Fan Yang Yu Liu Huaidong Min Zhiqiang Zhou Bin Zhou Yang Lei Wei Hu |
| author_facet | Zhichun Yang Fan Yang Yu Liu Huaidong Min Zhiqiang Zhou Bin Zhou Yang Lei Wei Hu |
| author_sort | Zhichun Yang |
| collection | DOAJ |
| description | The selection of the optimal 35 kV network structure is crucial for modern distribution networks. To address the problem of balancing investment costs and reliability benefits, as well as to establish the target network structure, firstly, the investment cost of the distribution network is calculated based on the determined number of network structure units. Secondly, reliability benefits are measured by combining the comprehensive function of user outage losses with the System Average Interruption Duration Index (SAIDI). Then, a multi-objective planning model of the network structure is established, and the weighted coefficient transformation method is used to convert reliability benefits and investment costs into the total cost of power supply per unit load. Finally, by using the influencing factors of the network structure as the initial population and setting the minimum total cost of the unit load as the fitness function, the DE algorithm is employed to obtain the optimal grid structure under continuous load density intervals. Case studies demonstrate that different load densities correspond to different optimal network structures. For load densities ranging from 0 to 30, the selected optimal network structures from low to high are as follows: overhead single radial, overhead three-section with two ties, cable single ring network, and cable dual ring network. |
| format | Article |
| id | doaj-art-2f43a20312694d8d9a845fcb3c0cbd60 |
| institution | OA Journals |
| issn | 1996-1073 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-2f43a20312694d8d9a845fcb3c0cbd602025-08-20T02:08:15ZengMDPI AGEnergies1996-10732024-11-011722576310.3390/en17225763The Intelligent Sizing Method for Renewable Energy Integrated Distribution NetworksZhichun Yang0Fan Yang1Yu Liu2Huaidong Min3Zhiqiang Zhou4Bin Zhou5Yang Lei6Wei Hu7Electric Power Research Institute of State Grid Hubei Co., Ltd., Wuhan 430037, ChinaElectric Power Research Institute of State Grid Hubei Co., Ltd., Wuhan 430037, ChinaElectric Power Research Institute of State Grid Hubei Co., Ltd., Wuhan 430037, ChinaElectric Power Research Institute of State Grid Hubei Co., Ltd., Wuhan 430037, ChinaState Grid HuBei Electric Power Co., Ltd., Wuhan 430037, ChinaState Grid HuBei Electric Power Co., Ltd., Wuhan 430037, ChinaElectric Power Research Institute of State Grid Hubei Co., Ltd., Wuhan 430037, ChinaElectric Power Research Institute of State Grid Hubei Co., Ltd., Wuhan 430037, ChinaThe selection of the optimal 35 kV network structure is crucial for modern distribution networks. To address the problem of balancing investment costs and reliability benefits, as well as to establish the target network structure, firstly, the investment cost of the distribution network is calculated based on the determined number of network structure units. Secondly, reliability benefits are measured by combining the comprehensive function of user outage losses with the System Average Interruption Duration Index (SAIDI). Then, a multi-objective planning model of the network structure is established, and the weighted coefficient transformation method is used to convert reliability benefits and investment costs into the total cost of power supply per unit load. Finally, by using the influencing factors of the network structure as the initial population and setting the minimum total cost of the unit load as the fitness function, the DE algorithm is employed to obtain the optimal grid structure under continuous load density intervals. Case studies demonstrate that different load densities correspond to different optimal network structures. For load densities ranging from 0 to 30, the selected optimal network structures from low to high are as follows: overhead single radial, overhead three-section with two ties, cable single ring network, and cable dual ring network.https://www.mdpi.com/1996-1073/17/22/5763network structureinvestment costdifferential evolution algorithmnetwork structure planningreliability benefit |
| spellingShingle | Zhichun Yang Fan Yang Yu Liu Huaidong Min Zhiqiang Zhou Bin Zhou Yang Lei Wei Hu The Intelligent Sizing Method for Renewable Energy Integrated Distribution Networks Energies network structure investment cost differential evolution algorithm network structure planning reliability benefit |
| title | The Intelligent Sizing Method for Renewable Energy Integrated Distribution Networks |
| title_full | The Intelligent Sizing Method for Renewable Energy Integrated Distribution Networks |
| title_fullStr | The Intelligent Sizing Method for Renewable Energy Integrated Distribution Networks |
| title_full_unstemmed | The Intelligent Sizing Method for Renewable Energy Integrated Distribution Networks |
| title_short | The Intelligent Sizing Method for Renewable Energy Integrated Distribution Networks |
| title_sort | intelligent sizing method for renewable energy integrated distribution networks |
| topic | network structure investment cost differential evolution algorithm network structure planning reliability benefit |
| url | https://www.mdpi.com/1996-1073/17/22/5763 |
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